Imaging salt with turning seismic waves

Geophysics ◽  
1992 ◽  
Vol 57 (11) ◽  
pp. 1453-1462 ◽  
Author(s):  
Dave Hale ◽  
N. Ross Hill ◽  
Joe Stefani
Keyword(s):  
Seismic Waves ◽  
Computational Cost ◽  
Salt Dome ◽  
Seismic Survey ◽  
Seismic Wave Velocity ◽  
Salt Domes ◽  
Reflection Time ◽  
Before And After ◽  
Migration Method ◽  
Geometrical Argument

Turning seismic waves, which first travel downward and then upward before (and after) reflection, have been recorded in a 3-D seismic survey conducted over an overhanging salt dome. Careful processing of these turning waves enables the imaging of the underside of the salt dome and of intrusions of salt into vertical faults radiating from the dome. When seismic wave velocity increases with depth, waves that initially travel downward are reflected and may turn so as to travel upward before reflection. A simple geometrical argument suggests that these turning waves are likely to exhibit abnormal moveout in common‐midpoint (CMP) gathers, in that reflection time decreases with increasing source‐receiver offset. This abnormal moveout and the attenuation of turning waves by most migration methods suggest that conventional seismic processing does not properly image turning waves. The most important step in imaging turning waves, assuming that they have been recorded, is the migration process. Simple and inexpensive modifications to the conventional phase‐shift migration method enable turning waves to be imaged for little additional computational cost. The examples provided in this paper suggest that these and other such modifications to conventional processing should be used routinely when imaging salt domes.

scholarly journals Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Gaoyang Li ◽  
Haoran Wang ◽  
Mingzi Zhang ◽  
Simon Tupin ◽  
Aike Qiao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Artery Bypass ◽  
Computational Cost ◽  
Specific Model ◽  
Arterial System ◽  
Patient Specific ◽  
Cardiovascular Hemodynamics ◽  
Before And After ◽  
Deep Learning Network ◽  
Cfd Method

AbstractThe clinical treatment planning of coronary heart disease requires hemodynamic parameters to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in the simulation of cardiovascular hemodynamics. However, for the patient-specific model, the complex operation and high computational cost of CFD hinder its clinical application. To deal with these problems, we develop cardiovascular hemodynamic point datasets and a dual sampling channel deep learning network, which can analyze and reproduce the relationship between the cardiovascular geometry and internal hemodynamics. The statistical analysis shows that the hemodynamic prediction results of deep learning are in agreement with the conventional CFD method, but the calculation time is reduced 600-fold. In terms of over 2 million nodes, prediction accuracy of around 90%, computational efficiency to predict cardiovascular hemodynamics within 1 second, and universality for evaluating complex arterial system, our deep learning method can meet the needs of most situations.

scholarly journals Wind Turbine Noise Reduction from Seismological Data

2021 ◽  
Author(s):  
Janis Heuel ◽  
Wolfgang Friederich
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Computational Cost ◽  
Noise Signal ◽  
Noise Model ◽  
Threshold Function ◽  
High Signal ◽  
Time Data ◽  
Negative Effects ◽  
Before And After

<p>Over the last years, installations of wind turbines (WTs) increased worldwide. Owing to<br>negative effects on humans, WTs are often installed in areas with low population density.<br>Because of low anthropogenic noise, these areas are also well suited for sites of<br>seismological stations. As a consequence, WTs are often installed in the same areas as<br>seismological stations. By comparing the noise in recorded data before and after<br>installation of WTs, seismologists noticed a substantial worsening of station quality leading<br>to conflicts between the operators of WTs and earthquake services.</p><p>In this study, we compare different techniques to reduce or eliminate the disturbing signal<br>from WTs at seismological stations. For this purpose, we selected a seismological station<br>that shows a significant correlation between the power spectral density and the hourly<br>windspeed measurements. Usually, spectral filtering is used to suppress noise in seismic<br>data processing. However, this approach is not effective when noise and signal have<br>overlapping frequency bands which is the case for WT noise. As a first method, we applied<br>the continuous wavelet transform (CWT) on our data to obtain a time-scale representation.<br>From this representation, we estimated a noise threshold function (Langston & Mousavi,<br>2019) either from noise before the theoretical P-arrival (pre-noise) or using a noise signal<br>from the past with similar ground velocity conditions at the surrounding WTs. Therefore, we<br>installed low cost seismometers at the surrounding WTs to find similar signals at each WT.<br>From these similar signals, we obtain a noise model at the seismological station, which is<br>used to estimate the threshold function. As a second method, we used a denoising<br>autoencoder (DAE) that learns mapping functions to distinguish between noise and signal<br>(Zhu et al., 2019).</p><p>In our tests, the threshold function performs well when the event is visible in the raw or<br>spectral filtered data, but it fails when WT noise dominates and the event is hidden. In<br>these cases, the DAE removes the WT noise from the data. However, the DAE must be<br>trained with typical noise samples and high signal-to-noise ratio events to distinguish<br>between signal and interfering noise. Using the threshold function and pre-noise can be<br>applied immediately on real-time data and has a low computational cost. Using a noise<br>model from our prerecorded database at the seismological station does not improve the<br>result and it is more time consuming to find similar ground velocity conditions at the<br>surrounding WTs.</p>

Measuring floating ice thickness with optical fibers and DAS, a test case study on a frozen moutain lake.

2021 ◽  
Author(s):  
Olivier Coutant ◽  
Ludovic Moreau ◽  
Pierre Boué ◽  
Eric Larose ◽  
Arnaud Cimolino
Keyword(s):  
Fiber Optics ◽  
Optical Fibers ◽  
Ambient Noise ◽  
Seismic Waves ◽  
Safety Issue ◽  
Seismic Survey ◽  
Ice Thickness ◽  
Test Case ◽  
Monitoring Method

<p>Accurate monitoring of floating ice thickness is an important safety issue for northern countries where lakes, fjords, and coasts are covered with ice in winter, and used by people to travel. For example in Finland, 15-20 fatal accidents occur every year due to ice-related drowning. We have explored the potential of fiber optics to measure the propagation of seismic waves guided in the ice layer, in order to infer its thickness via the inversion of the dispersion curves. An optical fiber was deployed on a frozen lake at Lacs Roberts (2400m) above Grenoble and we measured with a DAS the signal generated by active sources (hammer) and ambient noise. We demonstrate that we can retrieve the ice thickness. This monitoring method could be of interest since the deployment of a fiber on ice is quite simple (e.g. using a drone) compared to other techniques for ice thickness estimation such as seismic survey or manual drilling.</p>

Multiwave Seismic Survey under Conditions of Salt-Dome Tectonics of the South of Cis-Ural Trough

2006 ◽  
Author(s):  
B.Y. Meltchouk ◽  
S.M. Karnaukhov ◽  
I.A. Chirkin ◽  
S.L. Aroutunov ◽  
A.E. Suntsov ◽  
...  
Keyword(s):  
Salt Dome ◽  
Seismic Survey ◽  
The South

Technical and Economic Evaluation of Nominal 280 MW Compressed Air Energy Storage Plant in Salt Dome

1994 ◽  
Author(s):  
Alex Morrison ◽  
Bhupen Mehta ◽  
J. W. Lyons ◽  
Gregor Gnaedig
Keyword(s):  
Economic Evaluation ◽  
Energy Storage ◽  
Salt Dome ◽  
Compressed Air ◽  
Compressed Air Energy Storage ◽  
Economic Data ◽  
Cost Analyses ◽  
Weekly Cycle ◽  
Salt Domes ◽  
Operation And Maintenance

This paper summarizes the results of the technical and economic data of nominal 280 MW Compressed Air Energy Storage Plants (CAES) using caverns in salt domes located in southeastern parts of Mississippi for intermediate duty generation of 1,000 hours per year and peaking duty generation of 750 hours per year. The plants are assumed to operate 90% time on Natural Gas and 10% of the time on No. 2 distillate. A weekly cycle of 10 hours of generation and 12 hours of charging daily with 15 hours of weekend charging was the basis for the study. The study includes conceptual layout, optimization, detailed cost analyses, reliability and operation and maintenance of the Compressed Air Energy storage plant. The objective of the study is low capital cost of the CAES plant and optimum performance.

scholarly journals Technical NoteEarthquake dates and water level changes in wells in the Eskisehir region, Turkey

2003 ◽  
Vol 7 (5) ◽  
pp. 777-781 ◽  
Author(s):  
G. Yuce ◽  
D. Ugurluoglu
Keyword(s):  
Earthquake Prediction ◽  
Seismic Waves ◽  
North Anatolian Fault Zone ◽  
Groundwater Levels ◽  
Unconfined Aquifers ◽  
The North ◽  
Water Level Changes ◽  
Before And After ◽  
Aquifer Characteristics ◽  
Mechanical Investigation

Abstract. Although satisfactory results have yet to be obtained in earthquake prediction, one of the most common indicators of an anomalous precursor is a change in groundwater level in existing wells. Further wells should thus be drilled in unconfined aquifers since these are more susceptible to seismic waves. The Eskisehir region lies in the transition zone between the Aegean extensional domain and the compressible northern Anatolian block. Limnigraphs, installed in 19 exploration wells in the Eskisehir region, recorded pre-seismic, co-seismic and post-seismic level changes during the earthquakes of 17 August Izmit (Mw= 7.4) and 12 November Duzce (Mw= 7.2) 1999 that occurred along the North Anatolian Fault Zone. The Izmit and Duzce earthquakes affected groundwater levels, especially in confined aquifers. The aquifer characteristics before and after the earthquakes were unchanged so the aquifer is elastic in its behaviour. Further detailed geo-mechanical investigation of the confined aquifer in the Eskisehir region may improve understanding of earthquake prediction. Keywords: earthquake prediction, Eskisehir, hydrological warning, monitoring groundwater levels

Acoustic Assessment of Populations of Common Dolphin Delphinus Delphis In Conjunction With Seismic Surveying

1996 ◽  
Vol 76 (3) ◽  
pp. 811-820 ◽  
Author(s):  
John C. Goold
Keyword(s):  
Seismic Survey ◽  
Avoidance Reaction ◽  
Common Dolphin ◽  
Survey Area ◽  
Delphinus Delphis ◽  
Air Gun ◽  
Before And After ◽  
Seismic Surveying ◽  
Acoustic Contact ◽  
Common Dolphins

Common dolphin, Delphinus delphis (bairdi), were monitored acoustically across a survey area of 2747 km2 during a three month period before, during and after an oil industry two dimensional (2D) seismic reflection survey. Over 900 h of audio survey data were collected and analysed, along with GPS positional data, to reveal trends in presence and distribution of animals. The presence of dolphins was determined from vocalization events on the survey recordings. Dolphin presence was assessed by a system of percentage acoustic contact. This was highest before and after the seismic survey, with common dolphins showing a clear south-westerly skew within the survey area and a probable south-westerly migration of animals between September and December. Acoustic contact with dolphins during the seismic survey also showed a south-westerly skew within the survey area, although percentages were lower. Monitoring during the period of seismic activity was restricted to the immediate vicinity (1–2 km) of the seismic vessel, so percentage contact most likely reflects the response of dolphins to such immediate activity. The overall result suggests an avoidance reaction by common dolphins to air gun emissions, although certain observations suggest tolerance to these sounds outside a 1 km radius of the guns.

scholarly journals Prediction of Cerebral Aneurysm Hemodynamics With Porous-Medium Models of Flow-Diverting Stents via Deep Learning

2021 ◽  
Vol 12 ◽  
Author(s):  
Gaoyang Li ◽  
Xiaorui Song ◽  
Haoran Wang ◽  
Siwei Liu ◽  
Jiayuan Ji ◽  
...  
Keyword(s):  
Porous Medium ◽  
Deep Learning ◽  
Cerebral Aneurysm ◽  
Stent Placement ◽  
Point Cloud ◽  
Computational Cost ◽  
Learning Method ◽  
Method Error ◽  
Complex Operation ◽  
Before And After

The interventional treatment of cerebral aneurysm requires hemodynamics to provide proper guidance. Computational fluid dynamics (CFD) is gradually used in calculating cerebral aneurysm hemodynamics before and after flow-diverting (FD) stent placement. However, the complex operation (such as the construction and placement simulation of fully resolved or porous-medium FD stent) and high computational cost of CFD hinder its application. To solve these problems, we applied aneurysm hemodynamics point cloud data sets and a deep learning network with double input and sampling channels. The flexible point cloud format can represent the geometry and flow distribution of different aneurysms before and after FD stent (represented by porous medium layer) placement with high resolution. The proposed network can directly analyze the relationship between aneurysm geometry and internal hemodynamics, to further realize the flow field prediction and avoid the complex operation of CFD. Statistical analysis shows that the prediction results of hemodynamics by our deep learning method are consistent with the CFD method (error function <13%), but the calculation time is significantly reduced 1,800 times. This study develops a novel deep learning method that can accurately predict the hemodynamics of different cerebral aneurysms before and after FD stent placement with low computational cost and simple operation processes.

scholarly journals SPX Calibration of Option Approximations under Rough Heston Model

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2675
Author(s):  
Siow Woon Jeng ◽  
Adem Kiliçman
Keyword(s):  
Brownian Motion ◽  
Numerical Study ◽  
Computational Cost ◽  
Option Price ◽  
Padé Approximant ◽  
Heston Model ◽  
Approximation Formula ◽  
Approximation Methods ◽  
Pade Approximant ◽  
Before And After

The volatility of stock return does not follow the classical Brownian motion, but instead it follows a form that is closely related to fractional Brownian motion. Taking advantage of this information, the rough version of classical Heston model also known as rough Heston model has been derived as the macroscopic level of microscopic Hawkes process where it acts as a high-frequency price process. Unlike the pricing of options under the classical Heston model, it is significantly harder to price options under rough Heston model due to the large computational cost needed. Previously, some studies have proposed a few approximation methods to speed up the option computation. In this study, we calibrate five different approximation methods for pricing options under rough Heston model to SPX options, namely a third-order Padé approximant, three variants of fourth-order Padé approximant, and an approximation formula made from decomposing the option price. The main purpose of this study is to fill in the gap on lack of numerical study on real market options. The numerical experiment includes calibration of the mentioned methods to SPX options before and after the Lehman Brothers collapse.

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